{"paper":{"title":"Nested Sparse Approximation: Structured Estimation of V2V Channels Using Geometry-Based Stochastic Channel Model","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"math.OC","authors_text":"Erik G. Str\\\"om, Sajjad Beygi, Urbashi Mitra","submitted_at":"2014-12-09T15:37:59Z","abstract_excerpt":"Future intelligent transportation systems promise increased safety and energy efficiency. Realization of such systems will require vehicle-to-vehicle (V2V) communication technology. High fidelity V2V communication is, in turn, dependent on accurate V2V channel estimation. V2V channels have characteristics differing from classical cellular communication channels. Herein, geometry-based stochastic modeling is employed to develop a characterization of V2V channel channels. The resultant model exhibits significant structure; specifically, the V2V channel is characterized by three distinct regions "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1412.2999","kind":"arxiv","version":2},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}